Code works, but not as function. - R-help

Benjamin Ward (ENV) · 2012-11-16T01:48:35Z

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Thu, Nov 15, 2012 10:23 PM #

On Thu, Nov 15, 2012 at 5:48 PM, Benjamin Ward (ENV) <B.Ward at uea.ac.uk> wrote:

Hi,

I have some values in a list format generated by the following:
Path_Number <- 0010
ID.Path <- formatC(0001:Path_Number, width=4, flag=0) # Make vector of ID's.
No_of_Effectors <- sample(1:550, length(ID.Path), replace=TRUE) # Define Number of Effectors each individual gets.
Effectors <- split(sample(1:10000, sum(No_of_Effectors), replace=TRUE), rep(ID.Path, No_of_Effectors)) # Generate effectors and dish them out.
Effectors

And I've written a chunk which is designed to go through each element of the list, and then through each value in the element, and if a conditions is met (in this case if runif(1) is < 0.3, this is simple but may be changed later to be more complex probability criteria based on mutation data from experiment), change the value by 1 in either direction, higher or lower with equal probability. Here it is (I've changed the 0.3 value I mentioned to 0.9, so many values change so it can be easily seen):

l<-0 # Set counter 1 to 0.
for(i in Effectors){ # Begin loop on list of effectors.
  l2<-0 # Set counter 2 to 0.
  l <-l+1 # Increace counter number 1.
  for(i in Effectors[[l]]){ # Begin loop through all effector values.
    l2 <-l2+1 # Increace counter number 2.
    if(runif(1) < 0.9) ifelse(runif(1) <0.5, Effectors[[l]][l2] <- Effectors[[l]][l2]+1, Effectors[[l]][l2] <- Effectors[[l]][l2]-1) # Line which increaces or decreaces the values in the list element (50/50 chance of increace or decreace), if the first IF statement is satisfied.
  }
}

Now I don't know if this is the best and most R-ish way of doing this, but it works and I understand it. However I'd like to define a function with this, my attempts so far have been:

Eff.Mutate<-function(){
  l<-0 # Set counter 1 to 0.
  for(i in Effectors){ # Begin loop on list of effectors.
    l2<-0 # Set counter 2 to 0.
    l <-l+1 # Increace counter number 1.
    for(i in Effectors[[l]]){ # Begin loop through all effector values.
      l2 <-l2+1 # Increace counter number 2.
      if(runif(1) < 0.9) ifelse(runif(1) <0.5, Effectors[[l]][l2] <- Effectors[[l]][l2]+1, Effectors[[l]][l2] <- Effectors[[l]][l2]-1) # Line which increaces or decreaces the values in effvec, if the first IF statement is satisfied.
    }
  }
}

and:

Eff.Mutate2<-function(x){
  l<-0
  for(i in x){
    l2<-0
    l<-l+1
    for(i in x[[l]]){
      l2<-l2+1
      if(runif(1) < 0.9) ifelse(runif(1) <0.5, x[[l]][l2] <- x[[l]][l2]+1, x[[l]][l2] <- x[[l]][l2]-1)
    }
  }
}

However if I do either Eff.Mutate() or Eff.Mutate2(Effectors), then neither seems to work; I've seen no differences in the values in the list elements, before and after.
I can't figure out why it works as a code chunk but if I try to make it a function nothing seems to happen. I'm probably going about making it a function wrong.

The problem is that R functions do not operate on objects in the
global environment, where your list lives. They make a copy and
operate on that copy; when the function exists, that local copy is
discarded.

Here's a very simple example:

# Function to change a
change.a.wrong = function(new.a)
{
  a = new.a;
  print(paste("Changed value of a to", a))
}

#Initialize a to 1
a = 1

# change it to 5
change.a.wrong(5)

# but a is still 1!
a
[1] 1

The local copy of a is changed to 5, but discarded and the global copy
whose value is still 1 lives on.

The solution is to return the value of the variable you have changed,
and assign it to the original name. In your case you would define a
function

Eff.Mutate = function(x)
{
  ...your code changes x
  return(x)
}

and you would call it as

effectors.new = Eff.Mutate(effectors)

or so.

HTH,

Peter